Kevin Korb

Causal Discovery of Dynamic Bayesian Networks

Springer eBooks, 2012

 (Stochastic) search and score  Learning programs/packages: e.g. CaMML (Causal discovery via MM... more

Attention During Argument Generation And Presentation

International Conference on Natural Language Generation, 1998

We describe the operation of our argumentation system, and discuss its use of attentional focus d... more We describe the operation of our argumentation system, and discuss its use of attentional focus during both content planning and argument presentation. During content planning, attentional focus guides an abductive process used to build-up arguments. This process is applied to a model of a user's • beliefs and a normative model. During argument presentation, attentional focus supports the generation of enthymematic arguments.

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A Bayesian approach to automating argumentation

Our argumentation system NAG uses Bayesian networks in a user model and in a normative model to a... more Our argumentation system NAG uses Bayesian networks in a user model and in a normative model to assemble and assess nice arguments, that is arguments which balance persuasiveness with normative correctness. Attentional focus is simulated in both models to select relevant subnetworks for Bayesian propagation. Bayesian propagation in the user model is modified to represent some human cognitive weaknesses. The subnetworks are expanded in an iterative abductive process until argumentative goals are achieved in both models, when the argument is presented to the user.

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Developing an ontology for the meteorological forecasting process

Decision Support Systems, 2004

Developing An Ontology for the Meteorological Forecasting Process. John Bally*. Tal Boneh+. Ann E... more

ALife investigation of parental investment in reproductive strategies

Many organisms nourish and care for their offspring, boosting the offspring's reproductive potent... more Many organisms nourish and care for their offspring, boosting the offspring's reproductive potential. Trivers (1972) recognized that such parental investment, when made differentially across the sexes, could explain the existence of sexually dimorphic behaviour. However, parental investment in nature is difficult to measure, and explanations involving parental investment are hard to verify. Here we use an ALife simulation to investigate the effect of explicit, numerical parental investments on two reproductive strategies of interestconsensual mating and rape. With some preliminary empirical results, we demonstrate the potential of an ALife approach to evolutionary psychology.

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Bayesian network meta-models from combat simulation for Defence decision analysis

El Sawah, S. (ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation., 2019

Defence Science and Technology Group (DST) is investigating the characteristics of Land Combat Ve... more Defence Science and Technology Group (DST) is investigating the characteristics of Land Combat Vehicles (LCVs) with a view to improving purchasing decisions between different LCV options. Using a combination of closed-loop combat simulation (i.e., one run without any human interventions) and subject matter experts (SMEs), these studies seek to understand the close combat capability factors for a future LCV. These factors are being investigated for different kinds of physical environment and different levels of enemy lethality, with each LCV's lethality, survivability, signature (the ease with which the enemy identifies friendly forces) and knowledge acquisition (friendly forces identifying enemies) being measured, yielding a multi-dimensional view of the different LCVs and their performance. Our study describes a new approach, developing a Bayesian network (BN) meta-model (i.e., a model based upon the combat simulation model; see Fig 1) that combines those multiple dimensions in a single multicriterial decision model.

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Omnigram Explorer: A Simple Interactive Tool for the Initial Exploration of Complex Systems

07/20/2015-07/24/2015, 2015

We describe the design of Omnigram Explorer (OMG), an open-source tool for the interactive explor... more We describe the design of Omnigram Explorer (OMG), an open-source tool for the interactive exploration of relationships between variables in a complex system. OMG is designed to help researchers gain a holistic, qualitative understanding of the relationships between variables in their data at a preliminary stage of analysis; such exploration might highlight interactions that warrant further quantitative investigation using other tools. We illustrate OMG's use on real-world data, and also describe its potential as a tool for communication to non-specialists.

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Digital Genesis: Computers, Evolution and Artificial Life

The application of evolution in the digital realm, with the goal of creating artificial intellige... more The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting with the early theoretical work of John von Neumann and the pioneering experimental work of Nils Aall Barricelli. We argue that evolutionary thinking and artificial life will continue to play an integral role in the future development of the digital world.

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An ALife Investigation of Parental Investment

ABSTRACT Many organisms nourish and care for their offspring, boosting the offspring&#39;s re... more ABSTRACT Many organisms nourish and care for their offspring, boosting the offspring&#39;s reproductive potential. Trivers (1972) recognized that such parental investment, when made differentially across the sexes, could explain the existence of sexually dimorphic behaviour. However, parental investment in nature is difficult to measure, and explanations involving parental investment are hard to verify. Here we use an ALife simulation to investigate the effect of explicit, numerical parental investments on two reproductive strategies of interest -- consensual mating and rape. With some preliminary empirical results, we demonstrate the potential of an ALife approach to evolutionary psychology.

Causal interaction in Bayesian networks

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Why don't we practice what we teach? Engineering Software for Computer Science Research in Academia

The development process used by academic researchers often seems unsystematic. A Software Develop... more The development process used by academic researchers often seems unsystematic. A Software Development Life Cycle (SDLC) is seldom considered, commenting is scarce, and external documentation consists of erasure marks left on whiteboards. Configuration management is paid lip-service, but is not standard practice. This paper examines reasons behind the apparent large-scale non-adoption of software engineering in academic research. The effects where it was adopted are examined. Finally, we present an SDLC designed for the academic research environment.

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Learning Abnormal Vessel Behaviour from AIS Data with Bayesian Networks at Two Time Scales

In recent years, electronic vessel tracking has provided abundant data on vessel movements to sur... more In recent years, electronic vessel tracking has provided abundant data on vessel movements to surveillance authorities. Researchers have begun looking at the use of this data for anomaly detection using a wide variety of data mining techniques. Here we tackle anomaly detection with Bayesian Networks, training them with real world AIS data and producing models at two different time scales-both moment to moment and for the track as a whole. The networks also incorporate additional real world data, including weather, vessel details and details about vessel interactions. We find that the generated networks are quite easy to examine and verify despite incorporating a large number of variables; that combining models at the two different scales improves performance in a variety of cases; and, ultimately, that Bayesian Networks prove a promising approach to anomaly assessment and detection.

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Alife investigation of parental investment in reproductive strategies

Many organisms nourish and care for their offspring, boosting the offspring's reproductive potent... more Many organisms nourish and care for their offspring, boosting the offspring's reproductive potential. Trivers (1972) recognized that such parental investment, when made differentially across the sexes, could explain the existence of sexually dimorphic behaviour. However, parental investment in nature is difficult to measure, and explanations involving parental investment are hard to verify. Here we use an ALife simulation to investigate the effect of explicit, numerical parental investments on two reproductive strategies of interestconsensual mating and rape. With some preliminary empirical results, we demonstrate the potential of an ALife approach to evolutionary psychology.

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Epidemiological data mining of cardiovascular Bayesian networks

Bayesian networks (BNs) are rapidly becoming a leading tool for applied Artificial Intelligence. ... more Bayesian networks (BNs) are rapidly becoming a leading tool for applied Artificial Intelligence. Although BNs have been used successfully for many medical diagnosis problems, there have been few applications to epidemiological data where data mining methods play a significant role. In this paper, we look at the application of BNs to epidemiological data, specifically assessment of risk for coronary heart disease (CHD). We build the BNs: (1) by knowledge engineering BNs from two epidemiological models of CHD in the literature; (2) by applying a causal BN learner. We evaluate these BNs using cross-validation. We compared performance in predicting CHD events over 10 years, measuring area under the ROC curve and Bayesian information reward. The knowledge engineered BNs performed as well as logistic regression, while being easier to interpret. These BNs will serve as the baseline in future efforts to extend BN technology to better handle epidemiological data, specifically to model CHD.

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Causal reasoning with causal models

Under submission to S …, 2005

Page 1. Causal Reasoning with Causal M odels Kevin B. Korb, Charles R. Twardy,* Toby Handfield an... more

Software Engineering for Computer Science Research-Facilitating Improved Research Outcomes

by Andre Oboler and Kevin Korb

International Journal of …, Jan 1, 2004

Informative Interventions

Causal discovery programs have met with considerable enthu- siasm in the AI and data mining commu... more Causal discovery programs have met with considerable enthu- siasm in the AI and data mining communities. Amongst philosophers they have met a more mixed response, with numerous skeptics pointing out weak- nesses in their assumptions. Some criticize the reliance upon faithfulness (the idea that every causal connection will result in probab ilistic dependence), since the true model may in fact

Data mining cardiovascular Bayesian networks

by Kevin Korb and Charles R Twardy

Bayesian networks (BNs) are rapidly becoming a tool of choice for applied Artificial Intelligence... more Bayesian networks (BNs) are rapidly becoming a tool of choice for applied Artificial Intelligence. Although BNs have been successfully used for many medical diagnosis problems, there have been few applications to epidemiological data where data mining methods play a significant role. In this paper, we look at the application of BNs to epidemiological data, specif- ically assessment of risk for

Knowledge engineering cardiovascular Bayesian networks from the literature

by Kevin Korb and Charles R Twardy

Bayesian networks are rapidly becoming a tool of choice for applied Artificial Intelligence. Ther... more Bayesian networks are rapidly becoming a tool of choice for applied Artificial Intelligence. There have been many medical applications of BNs however few applying data mining methods to epidemiology. In a previous study we looked at such an application to epidemiologi- cal data, specifically assessment of risk for coronary heart disease. In that previous study, we featured two Bayesian networks

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Perambulations on the Way to an Architecture for a Nice Argument Generator

by I. Zukerman and Kevin Korb

We introduce the architecture and organizational princi- ples of a system capable of analyzing an... more We introduce the architecture and organizational princi- ples of a system capable of analyzing and composing arguments that are persuasive for particular interlocutors. The main components of this system are an Argument Generator, Analyzer and Strategist. The Generator produces arguments that aim to convince a user of the correctness of a goal proposition. Since the generated arguments are tailored to

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